Method and system for diagnosing a semiconductor wafer

ABSTRACT

Methods and systems for diagnosing a semiconductor wafer are provided. A plurality of raw images are captured with a tilt angle from the semiconductor wafer according to graphic data system (GDS) information regarding a layout of a target die, by an inspection apparatus. A first image-based comparison is performed on the plurality of raw images, by a determining circuitry, to obtain a defect image in the plurality of raw images. A second image-based comparison is performed on a reference image and the defect image, so as to classify a defect type of an image difference in the defect image, by the determining circuitry. The number of the plurality of raw images is greater than 2.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a Continuation of application Ser. No. 17/000,609,filed on Aug. 24, 2020, which is a Continuation of application Ser. No.15/919,428, filed on Mar. 13, 2018, now U.S. Pat. No. 10,755,405, whichclaims priority of U.S. Provisional Application No. 62/590,407, filed onNov. 24, 2017, the entirety of which are incorporated by referenceherein.

BACKGROUND

In semiconductor technology, the wafers, each having multiple dies, areproduced by a plurality of processes and stages in a wafer fabricationfacility (FAB). Each process or stage may introduce one or more defectsinto the semiconductor wafer, which leads to quality and reliabilityissues, failures, and yield losses. To improve manufacturing technologyand enhance wafer quality, reliability, and yield, the semiconductorwafers are measured, tested, monitored, and diagnosed at each processand at each stage.

BRIEF DESCRIPTION OF THE DRAWINGS

Aspects of the present disclosure are best understood from the followingdetailed description when read with the accompanying figures. It shouldbe noted that, in accordance with the standard practice in the industry,various features are not drawn to scale. In fact, the dimensions of thevarious features may be arbitrarily increased or reduced for clarity ofdiscussion.

FIG. 1 shows a semiconductor wafer 100 to be inspected, in accordancewith some embodiments of the disclosure.

FIG. 2 shows a simplified flowchart of a method for diagnosing thesemiconductor wafer of FIG. 1 , in accordance with some embodiments ofthe disclosure.

FIG. 3 shows a semiconductor wafer to be inspected, in accordance withsome embodiments of the disclosure.

FIGS. 4A-4C show schematic views illustrating various examples of theraw images obtained from the dies of the semiconductor wafer of FIG. 3 .

FIG. 5 shows a semiconductor wafer to be inspected, in accordance withsome embodiments of the disclosure.

FIG. 6 shows a schematic view illustrating an example of a memory arrayof the target die corresponding to the areas in the semiconductor waferof FIG. 5 , in accordance with some embodiments of the disclosure.

FIGS. 7A-7C show schematic views illustrating various examples of theraw images obtained from the memory array of FIG. 6 .

FIG. 8 shows a simplified diagram of a system for diagnosing asemiconductor wafer, in accordance with some embodiments of thedisclosure.

FIG. 9 shows a schematic view illustrating the inspection apparatus ofFIG. 8 , in accordance with some embodiments of the disclosure.

FIG. 10A shows a schematic view illustrating an example of the raw imageobtained by the first image capturing device of FIG. 9 .

FIG. 10B shows a schematic view illustrating an example of the raw imageobtained by the second image capturing device of FIG. 9 .

DETAILED DESCRIPTION

The following disclosure provides many different embodiments, orexamples, for implementing different features of the subject matterprovided. Specific examples of components and arrangements are describedbelow to simplify the present disclosure. These are, of course, merelyexamples and are not intended to be limiting. For example, the formationof a first feature over or on a second feature in the description thatfollows may include embodiments in which the first and second featuresare formed in direct contact, and may also include embodiments in whichadditional features may be formed between the first and second features,such that the first and second features may not be in direct contact. Inaddition, the present disclosure may repeat reference numerals and/orletters in the various examples. This repetition is for the purpose ofsimplicity and clarity and does not in itself dictate a relationshipbetween the various embodiments and/or configurations discussed.

Some variations of the embodiments are described. Throughout the variousviews and illustrative embodiments, like reference numbers are used todesignate like elements. It should be understood that additionaloperations can be provided before, during, and/or after a disclosedmethod, and some of the operations described can be replaced oreliminated for other embodiments of the method.

In integrated circuit (IC) design, a variety of functions are integratedinto one chip, and an application specific integrated circuit (ASIC) orsystem on a chip (SOC) cell based design is often used. In thisapproach, a library of known functions is provided, and after thefunctional design of the device is specified by choosing and connectingthese standard functions, and proper operation of the resulting circuitis verified using electronic design automation (EDA) tools, the libraryelements are mapped on to predefined layout cells, which containprefigured elements such as transistors. The cells are chosen with theparticular semiconductor process features and parameters in mind tocreate a process parameterized physical representation of the design.The design flow continues from that point by performing placement androuting of the local and global connections needed to form the completeddesign using the standard cells.

After design rule checks, design rule verification, timing analysis,critical path analysis, static and dynamic power analysis, and finalmodifications to the design, a tape-out process is performed to producephotomask generation data. This photomask generation (PG) data is thenused to create the optical masks used to fabricate the semiconductordevice in a photolithographic process at a wafer fabrication facility(FAB). In the tape-out process, the database file of the IC is convertedinto a Graphic Database System (GDS) file (e.g. a GDS file or a GDSIIfile). The GDS file is then used to make various layers of masks forintegrated circuit manufacturing. Specifically, the GDS file became theindustry's standard format for transfer of IC layout data between designtools of different vendors.

Inspection processes are used in various steps of the semiconductormanufacturing process to detect defects on wafers according to GDSfiles, so as to promote higher yield in the manufacturing process andthus higher profits. Furthermore, as the dimensions of semiconductordevices decrease, inspection becomes even more important to thesuccessful manufacture of acceptable semiconductor devices becausesmaller defects can cause the devices to fail. For instance, as thedimensions of semiconductor devices decrease, the detection of smallerdefects has become necessary since even relatively small defects maycause aberrations in the semiconductor devices. Moreover, as designrules shrink, semiconductor manufacturing processes may be operatingcloser to the limitations on the performance capability of theprocesses, and smaller defects can have an impact on the electricalparameters of the device.

FIG. 1 shows a semiconductor wafer 100 to be inspected, in accordancewith some embodiments of the disclosure. The semiconductor wafer 100includes multiple dies 110. The dies 110 are identical and separatedfrom each other by the scribing lines 115. During various processes, thesemiconductor wafer 100 is inspected to detect defects on the dies 110.The defects are related to insufficient space and/or line width margins.For example, a critical dimension of the semiconductor wafer 100, awidth or a length of a first feature (e.g. the width/length ofconductive line), or a distance between the first feature and a secondfeature (e.g. the space between two conductive lines, or active area).If an inspection result is normal, the subsequent process or stage isperformed on the semiconductor wafer 100. If the semiconductor wafer 100has not been completed, the next process is performed on thesemiconductor wafer 100. Similarly, after performing the next process,the semiconductor wafer 100 will be inspected again until all theprocesses of the semiconductor wafer 100 have been completed. If thesemiconductor wafer 100 has been completed, the semiconductor wafer 100is diced along the scribing lines 115, and the dies 110 are obtained.Next, multiple integrated circuits (ICs) are fabricated based on theobtained dies 110.

FIG. 2 shows a simplified flowchart of a method for diagnosing thesemiconductor wafer 100 of FIG. 1 , in accordance with some embodimentsof the disclosure. It should be noted that additional processes may beprovided before, during, and/or after the method of FIG. 2 , and thatsome processes may only be briefly described herein. Furthermore, themethod of FIG. 2 can be performed in one or more process or stage ofmanufacturing the semiconductor wafer 100. At least one semiconductorwafer 100 is inspected by an inspection apparatus. As described above,the semiconductor wafer 100 includes multiple dies 110. Furthermore, thedies 110 have the same circuits and the same structures corresponding toa target die.

In operation S10, when the semiconductor wafer 100 is inspected by theinspection apparatus, the inspection apparatus is capable of obtainingthree raw images IMGr_1, IMGr_2 and IMGr_3, such as more than two rawimages, from the semiconductor wafer 100 according to a GDS fileregarding a specific layout of the target die. In some embodiments, theinspection apparatus obtains the three raw images IMGr_1, IMGr_2 andIMGr_3 via optical, electron beam, UV light, visible light, invisiblelight, or laser surface scan. Furthermore, the specific layout of thetarget die represents the features (e.g., space and/or line width) ofthe target die prone to defects. In some embodiments, the raw imagesIMGr_1, IMGr_2 and IMGr_3 are captured from different dies 110 of thesemiconductor wafer 100. In some embodiments, the raw images IMGr_1,IMGr_2 and IMGr_3 are captured from the different positions in the samedie 110 of the semiconductor wafer 100. The relationships of the rawimages IMGr_1, IMGr_2 and IMGr_3 will be described below.

In operation S20, a first image-based comparison is performed on the rawimages IMGr_1, IMGr_2 and IMGr_3. After the first image-based comparisonis completed, a comparison result is obtained.

In operation S30, it is determined whether one of more image differencesare present between the raw images IMGr_1, IMGr_2 and IMGr_3 accordingto the comparison result obtained in operation S20.

If no image difference is detected in the first image-based comparisonof operation S20, the comparison result indicates that the raw imagesIMGr_1, IMGr_2 and IMGr_3 are the same. Next, the operation S10 of theflowchart in FIG. 2 is performed again, so as to obtain new raw imagesIMGr_1, IMGr_2 and IMGr_3. In some embodiments, the new raw imagesIMGr_1, IMGr_2 and IMGr_3 are captured from the dies 110 different fromthe dies 110 corresponding to the previous raw images IMGr_1, IMGr_2 andIMGr_3. In some embodiments, the new raw images IMGr_1, IMGr_2 or IMGr_3is captured from the identical die 110 corresponding to the previous rawimages IMGr_1, IMGr_2 or IMGr_3.

If an image difference between the raw images IMGr_1, IMGr_2 and IMGr_3is detected in the first mage-based comparison of operation S20, thecomparison result includes information regarding which raw image is adefect image having the image difference, and a location of the imagedifference in the defect image. In some embodiments, the raw imagehaving the image difference is assigned as the defect image.

If the defect image is detected from the raw images IMGr_1, IMGr_2 orIMGr_3, a second image-based comparison is performed on the defect imageand a reference image IMG_REF in operation S40. By comparing the defectimage with the reference image IMG_REF, the defect type of each imagedifference of the defect image is classified, thereby various defecttypes in the defect image can be detected when the second image-basedcomparison is performed. In some embodiments, the reference imageIMG_REF is the previous raw images IMGr_1, IMGr_2 or IMGr_3 without theimage difference.

In some embodiments, the reference image IMG_REF is captured from agolden wafer. The golden wafer is selected from a lot of semiconductorwafers 100, and the golden wafer is used as a template wafer to measure,test, monitor or diagnose the other semiconductor wafers 100 in the lotof semiconductor wafers 100. The reference image IMG_REF is used toperform measurement for the other semiconductor wafers 100, so as toverify these semiconductor wafers 100.

In some embodiments, the reference image IMG_REF is captured from agolden die 110 of the semiconductor wafer 100. The golden die isselected from a lot of dies 110 of the same semiconductor wafer 100, andthe golden die is used as a template die to measure, test, monitor ordiagnose the other dies 110 in the semiconductor wafer 100. Thereference image IMG_REF is used to perform measurement for the otherdies 110 of the semiconductor wafer 100, so as to verify these dies 110.

The reference image IMG_REF is a template for diagnosing thesemiconductor wafer 100 in a specific process or stage. In someembodiments, each process or stage has its own reference image IMG_REF.Moreover, the specific layout is a fractional layout of the target die.The fractional layout includes a multi-layer structure of the targetdie. In some embodiments, the reference image IMG_REF includesinformation regarding a pattern contour corresponding to the specificlayout in the semiconductor wafer 100.

The multi-layer structure includes a first layer having multiplefeatures, and a second layer having multiple features. Furthermore, thefirst layer is disposed on or under the second layer, and a cross-layerstructure is formed.

If the classified defect type has no effect on the die 110 correspondingto the defect image, the subsequent process or stage is performed on thesemiconductor wafer 100. If the classified defect type has a greatimpact on the die 110, an improvement procedure is performed throughmasks, layout and/or processes.

In some embodiments, when each raw image IMGr_1, IMGr_2 or IMGr_3 iscaptured from the semiconductor wafer 100, the second image-basedcomparison of operation S40 is performed on the captured raw image andthe reference image IMG_REF, so as to verify the semiconductor wafer100. Thus, the operations S20 and S30 of FIG. 2 may be omitted.

FIG. 3 shows a semiconductor wafer 100A to be inspected, in accordancewith some embodiments of the disclosure. The semiconductor wafer 100Aincludes the dies 110 a-110 f. In such embodiments, other dies areomitted in the semiconductor wafer 100A for simplicity of explanation.

The dies 110 a-110 f have the same circuits and the same structurescorresponding to a target die. Moreover, the dies 110 a-110 f haveindividual coordinates in the semiconductor wafer 100A. Furthermore,each of the dies 110 a-110 f has an area corresponding to a GDS fileregarding a specific layout of the target die. For example, the area 120a of the die 110 a has a first group of coordinates (e.g., X-coordinateand Y-coordinate) (or position) on the die 110 a, and the area 120 b ofthe die 110 b has a second group of coordinates (or position) on the die110 b. The first and second coordinates are the same for the dies 110 aand 110 b, i.e. the first and second groups of coordinates correspondingto the same features in the specific layout of the target die.

When the semiconductor wafer 100A of FIG. 3 is inspected by aninspection apparatus (in operation S10 of FIG. 2 ), the inspectionapparatus is configured to obtain the raw image IMGr_1 a (as shown inFIG. 4A) from the die 110 a, the raw image IMGr_2 a (as shown in FIG.4B) from the die 110 b, and the raw image IMGr_3 a (as shown in FIG. 4C)from the die 110 c in the semiconductor wafer 100 according to a GDSfile regarding the specific layout of the target die. In suchembodiments, the number of raw images IMGr_1 a, IMGr_2 a, and IMGr_3 ais used as an example. In some embodiments, the number of raw imagesbeing used to perform a first image-based comparison is greater than orequal to 3. As described above, the specific layout of the target dierepresents the features (e.g., space and/or line width) of the targetdie prone to defects. In response to the specific layout of the targetdie, the inspection apparatus captures the raw images corresponding tothe specific layout of a part of areas in the target die rather than thewhole target die. Therefore, tooling time of the inspection apparatus isdecreased for capturing the raw images. Furthermore, measurement isaccurate due to higher image resolution, thereby increasing the accuracyof comparison.

After obtaining the raw images IMGr_1 a, IMGr_2 a and IMGr_3 a, a firstimage-based comparison is performed on the raw images IMGr_1 a of FIG.4A, IMGr_2 a of FIG. 4B, and IMGr_3 a of FIG. 4C (in operation S20 ofFIG. 2 ). After the first image-based comparison is completed, it isdetermined that an image difference is present between the raw imagesIMGr_1 a, IMGr_2 a and IMGr_3 a (in operation S30 of FIG. 2 ). Forexample, a space 122_1 in the raw image IMGr_1 a of FIG. 4A is the sameas a space 122_3 in the raw image IMGr_3 a of FIG. 4C. Furthermore, thespace 122_1 in the raw image IMGr_1 a of FIG. 4A is shorter than a space122_2 in the raw image IMGr_2 a of FIG. 4B. Thus, a comparison result isobtained, and the comparison result includes information regarding thatthe raw image IMGr_2 a of FIG. 4B is assigned as a defect image havingthe image difference (e.g., the larger space 122_2), and the coordinates(or position) of the image difference in the raw image IMGr_2 a of FIG.4B.

In some embodiments, the image difference is obtained by comparing theshape difference of the features in the raw images IMGr_1 a, IMGr_2 aand IMGr_3 a. In some embodiments, the image difference is obtained bycomparing the difference between light and dark contrast of the featuresin the raw images IMGr_1 a, IMGr_2 a and IMGr_3 a.

After detecting that the image difference is present in the raw imageIMGr_2 a of FIG. 4B, a second image-based comparison is performed on theraw image IMGr_2 a of FIG. 4B and a reference image IMG_REF (inoperation S40 of FIG. 2 ), so as to classify the defect type of theimage difference in the raw image IMGr_2 a of FIG. 4B. As describedabove, the reference image IMG_REF is the previous raw image without theimage difference or a golden image captured from a golden wafer or agolden die.

If the classified defect type has no effect on the die 110 bcorresponding to the raw image IMGr_2 a of FIG. 4B, such as the size ofthe space 122_2 of FIG. 4B is within the allowable range, the remainingdies are diagnosed for the semiconductor wafer 100A. For example, theinspection apparatus is configured to obtain new raw image IMGr_1 (notshown) from the die 110 d, new raw image IMGr_2 (not shown) from the die110 e, and new raw image IMGr_3 (not shown) from the die 110 f in thesemiconductor wafer 100A of FIG. 3 , so as to perform a firstimage-based comparison on the raw image IMGr_1 from the die 110 d, theraw image IMGr_2 from the die 110 e, and the raw image IMGr_3 from thedie 110 f, and then the subsequent operations are performed according toa comparison result of the current first image-based comparison.

In some embodiments, if the classified defect type has no effect on thedie 110 b corresponding to the raw image IMGr_2 a of FIG. 4B, theremaining dies are diagnosed with the previous raw images without theimage difference (e.g., the raw image IMGr_1 a of FIG. 4A or the rawimage IMGr_3 a of FIG. 4C) for the semiconductor wafer 100A. Forexample, the inspection apparatus is configured to obtain the new rawimage IMGr_1 (not shown) from the die 110 d, and the new raw imageIMGr_2 (not shown) from the die 110 e in the semiconductor wafer 100A ofFIG. 3 , so as to perform a first image-based comparison on the rawimage IMGr_1 from the die 110 d, the raw image IMGr_2 from the die 110e, and the previous raw image IMGr_1 a of FIG. 4A or IMGr_3 a of FIG.4C, and then the subsequent operations are performed according to acomparison result of the current first image-based comparison.

FIG. 5 shows a semiconductor wafer 100B to be inspected, in accordancewith some embodiments of the disclosure. The semiconductor wafer 100Bincludes the dies 110 a and 110 b. In such embodiments, other dies areomitted in the semiconductor wafer 100B for simplicity of explanation.

The dies 110 a and 110 b have the same circuits and the same structurescorresponding to a target die. Furthermore, each of the dies 110 a and110 b has an area corresponding to a GDS file regarding a specificlayout of the target die. For example, the area 130 a of the die 110 ahas a first group of coordinates (or position) on the die 110 a, and thearea 130 b of the die 110 b has a second group of coordinates (orposition) on the die 110 b. The first and second groups of coordinatesare the same for the dies 110 a and 110 b, i.e. the first and secondgroups of coordinates corresponding to the same features in the specificlayout of the target die. In such embodiments, the areas 130 a and 130 bcorrespond to a specific circuit with duplicate layout, such as a memoryarray formed by multiple memory cells.

FIG. 6 shows a schematic view illustrating an example of a memory array135 of the target die corresponding to the areas 130 a and 130 b in thesemiconductor wafer 100B of FIG. 5 , in accordance with some embodimentsof the disclosure. The memory array 135 includes multiple memory cells132 arranged in rows and columns, and the memory cells 132 have the samecircuit and the same structure. For example, the memory array 135 is aSRAM memory array, and each memory cell 132 is a bit cell, such as asix-transistor (6T), 8T, 10T cell and so on.

When the semiconductor wafer 100B of FIG. 5 is inspected by aninspection apparatus (in operation S10 of FIG. 2 ), the inspectionapparatus is configured to obtain the raw image IMGr_1 b (as shown inFIG. 7A) from the area 140 a of the memory cell 132 a, the raw imageIMGr_2 b (as shown in FIG. 7B) from the area 140 b of the memory cell132 b, and the raw image IMGr_3 b (as shown in FIG. 7C) from the area140 c of the memory cell 132 c on the die 110 a according to a GDS fileregarding the specific layout of the target die. In such embodiments,the areas 140 a, 140 b and 140 c has the different coordinates (orpositions) on the die 110 a. Moreover, the memory cells 132 a-132 c haveindividual coordinates on the die 110 a. Furthermore, the specificlayout of the target die is a duplicate layout that represents thefeatures (e.g., space and/or line width) of the target die prone todefects. In response to the specific layout of the target die, theinspection apparatus captures the raw images corresponding to thespecific layout of a part of areas in the target die rather than thewhole target die. Therefore, tooling time of the inspection apparatus isdecreased for capturing the raw images. Furthermore, measurement isaccurate due to higher image resolution, thereby increasing the accuracyof comparison.

After obtaining the raw images IMGr_1 b, IMGr_2 b and IMGr_3 b, a firstimage-based comparison is performed on the raw images IMGr_1 b of FIG.7A, IMGr_2 b of FIG. 7B, and IMGr_3 b of FIG. 7C (in operation S20 ofFIG. 2 ). After the first image-based comparison is completed, it isdetermined whether one or more image differences are present between theraw images IMGr_1 b, IMGr_2 b and IMGr_3 b (in operation S30 of FIG. 2).

In some embodiments, due to higher image resolution, various featurescan be compared in the first image-based comparison. Thus, variousdefect types can be detected when the first image-based comparison isperformed. For example, in the first image-based comparison, the space142_1 shown in the raw image IMGr_1 b of FIG. 7A, the space 142_2 shownin the raw image IMGr_2 b of FIG. 7B, and the space 142_3 shown in theraw image IMGr_1 c of FIG. 7C can be compared in the first image-basedcomparison. Furthermore, the contour (of shape) 144_1 shown in the rawimage IMGr_1 b of FIG. 7A, the contour 144_2 shown in the raw imageIMGr_2 b of FIG. 7B, and the contour 144_3 shown in the raw image IMGr_3b of FIG. 7C can also be compared in the first image-based comparison.

As described above, if an image difference is present in the raw imageIMGr_1 b of FIG. 7A, IMGr_2 b of FIG. 7B or IMGr_3 b of FIG. 7C, asecond image-based comparison is performed on the defect image havingthe image difference and a reference image IMG_REF (in operation S40 ofFIG. 2 ), so as to classify the defect type of the image difference inthe defect image. In some embodiments, the current process or stage issuspended for checking according to the classified defect type of theimage difference.

In some embodiments, the image difference is obtained by comparing theshape difference of the features in the raw images IMGr_1 b, IMGr_2 band IMGr_3 b. In some embodiments, the image difference is obtained bycomparing the difference between light and dark contrast of the featuresin the raw images IMGr_1 b, IMGr_2 b and IMGr_3 b.

Conversely, if no image difference is present in the raw image IMGr_1 bof FIG. 7A, IMGr_2 b of FIG. 7B or IMGr_3 b of FIG. 7C, the remainingdies of the semiconductor wafer 100B are diagnosed, such as the die 110b.

FIG. 8 shows a simplified diagram of a system 200 for diagnosing asemiconductor wafer 100, in accordance with some embodiments of thedisclosure. The system 200 includes a processing circuitry 210,determining circuitry 220, and an inspection apparatus 230.

Multiple dies 110 will be implemented in the semiconductor wafer 100 viathe various processes and stages performed at a wafer fabricationfacility. When each process or stage is performed, the semiconductorwafer 100 will be verified and diagnosed via the system 200.

The semiconductor wafer 100 to be diagnosed is loaded in the inspectionapparatus 230. In some embodiments, the inspection apparatus 230 can bean image capturing mechanism, and the image capturing mechanism iscapable of capturing a raw image from the semiconductor wafer 100.

In some embodiments, the system 200 further includes an interface device250, and a database 240.

The processing circuitry 210 can obtain a graphic database system fileGDS of the target die to be implemented in the semiconductor wafer 100.In some embodiments, the file GDS is obtained from the database 240. Insome embodiments, the file GDS is obtained from a remote server.

Furthermore, the processing circuitry 210 can further obtain a userinput Din from the interface device 250. In some embodiments, the userinput Din includes information regarding coordinates and patterns proneto defects in the layout of the target die.

In the system 200, the processing circuitry 210 can obtain GDSinformation in the file GDS. In response to the information of the userinput Din, the processing circuitry 210 can clip the GDS information toprovide the clipped GDS information GDSc, thereby providing increasedflexibility based on improvement in handling customized requirements. Insome embodiments, the clipped GDS information GDSc includes theinformation regarding coordinates and patterns prone to defects in thelayout of the target die.

In some embodiments, the file GDS includes layout information about eachlayer of the target die of the semiconductor wafer 100. The processingcircuitry 210 can provide the clipped GDS information GDSc for thecorresponding layer of the semiconductor wafer 100.

The clipped GDS information GDSc includes little layout information,thus it is difficult to effectively and sufficiently gather informationfrom the clipped GDS information GDSc. Therefore, information regardingcircuit design and circuit layout of the target die can be kept secret.

In some embodiments, the processing circuitry 210 can provide theclipped GDS information GDSc to the inspection apparatus 230 via thedetermining circuitry 220. In some embodiments, the processing circuitry210 can be implemented in the determining circuitry 220.

In some embodiments, the processing circuitry 210 can obtain a referenceimage IMG_REF from the database 240 or the interface device 250, andprovides the reference image IMG_REF to the determining circuitry 220for a second image-based comparison of operation S40 of FIG. 2 . Asdescribed above, the reference image IMG_REF is captured from a goldendie or a golden semiconductor wafer in advance.

According to the clipped GDS information GDSc, the inspection apparatus230 can capture the raw images IMGr_1, IMGr_2, and IMGr_3 from theloaded semiconductor wafer 100. For example, the inspection apparatus230 can perform a positioning operation so as to capture the raw imagesIMGr_1, IMGr_2, and IMGr_3 according to the coordinates within theclipped GDS information GDSc.

After capturing the raw images IMGr_1, IMGr_2, and IMGr_3, theinspection apparatus 230 outputs the raw images IMGr_1, IMGr_2, andIMGr_3 to the determining circuitry 220. Next, the determining circuitry220 can perform a first image-based comparison on the raw images IMGr_1,IMGr_2, and IMGr_3, so as to detect whether one or more imagedifferences are present between the raw images IMGr_1, IMGr_2 andIMGr_3.

In some embodiments, the image difference is obtained by comparing theshape difference of the features in the raw images IMGr_1, IMGr_2 andIMGr_3. In some embodiments, the image difference is obtained bycomparing the difference between light and dark contrast of the featuresin the raw images IMGr_1, IMGr_2 and IMGr_3.

If no image difference is detected in the first image-based comparison,the determining circuitry 220 can control the inspection apparatus 230to capture new raw images IMGr_1, IMGr_2 and IMGr_3 from thesemiconductor wafers 100. Furthermore, the determining circuitry 220provides a diagnostic result Result_Out to indicate that the raw imagesIMGr_1, IMGr_2 and IMGr_3 are the same.

If the image difference is present, the determining circuitry 220 canperform a second image-based comparison on the reference image IMG_REFand the defect image having one or more image differences, so as toclassify the defect types of the image differences in the defect image.As described above, the reference image IMG_REF is obtained from theprocessing circuitry 210 or the previous raw images IMGr_1, IMGr_2 andIMGr_3 from the inspection apparatus 230. In some embodiments, thedetermining circuitry 220 determines whether the classified defect typehas no effect on the die 110 having the image difference. According tothe classified result, the determining circuitry 220 can provide adiagnostic result Result_Out. In some embodiments, the diagnostic resultResult_Out indicates whether the defect type of the image difference isnormal.

If the diagnostic result Result_Out is normal, the features of thesemiconductor wafer 100 are normal in the current process or stage forthe semiconductor wafer 100. In response to the diagnostic resultResult_Out, the inspection apparatus 230 may continue to diagnose thesemiconductor wafer 100 until the dies 110 of the semiconductor wafer100 are diagnosed. Thus, the semiconductor wafer 100 is unloaded fromthe inspection apparatus 230 to perform subsequent processes/stages.Conversely, if the diagnostic result Result_Out is abnormal, i.e. thedefect is present in the semiconductor wafer 100, the current process orstage is suspended for checking the semiconductor wafer 100.

FIG. 9 shows a schematic view illustrating the inspection apparatus 230of FIG. 8 , in accordance with some embodiments of the disclosure. Theinspection apparatus 230 includes a first image capturing device 234Aand/or a second image capturing device 234B. The inspection apparatus230 is capable of capturing the raw images from the semiconductor wafer100 on a stage 232 via optical, electron beam, UV light, visible light,invisible light, or laser surface scan. In some embodiments, the firstimage capturing device 234A, the second image capturing device 234B orthe stage 232 is movable.

The first image capturing device 234A is arranged to face the topsurface of the semiconductor wafer 100, and is configured to capture theraw images (as shown in FIG. 10A) from the semiconductor wafer 100vertically. The second image capturing device 234B is arranged to facethe top surface of the semiconductor wafer 100 with a tilt angle θ, andis configured to capture the raw images (as shown in FIG. 10B) from thesemiconductor wafer 100 with the tilt angle θ.

FIG. 10A shows a schematic view illustrating an example of the raw imageobtained by the first image capturing device 234A of FIG. 9 . In FIG.10A, by detecting or comparing the raw images obtained by the firstimage capturing device 234A vertically, the defects (labeled as 150 a)will not be diagnosed due to the defects not being completely capturedin the raw images.

FIG. 10B shows a schematic view illustrating an example of the raw imageobtained by the second image capturing device 234B of FIG. 9 . In FIG.10B, by detecting or comparing the raw images obtained by the secondimage capturing device 234B with the tilt angle θ, the defects (labeledas 150 b) can be diagnosed and verify. Therefore, by capturing the rawimages at various tilt angles θ, the defects can be accuratelydiagnosed.

Embodiments for diagnosing a semiconductor wafer are provided. Multipleraw images are obtained according to GDS information of a target die ofthe semiconductor wafer. The number of raw images is more than two. Insome embodiments, the raw images are obtained from different dies of thesemiconductor wafer. In some embodiments, the raw images are obtainedfrom different positions in the same die of the semiconductor wafer. Afirst image-based comparison is performed on the raw images, so as todetect whether one or more image differences are present between the rawimages. If the image difference is present in one of the raw images, theraw image having the image difference is assigned as a defect image. Asecond image-based comparison is performed on a reference image and thedefect image, so as to classify the defect type of each imagedifference. In some embodiments, the reference image is the previous rawimage without the image difference or a golden image captured from agolden wafer or a golden die. Furthermore, measurement is accurate bycapturing the raw images in the semiconductor wafer according to the GDSinformation. Thus, process capability index (CPK) is stable, andmanufacturing cost (e.g. manpower and tooling time) is decreased.

In some embodiments, a method for diagnosing a semiconductor wafer isprovided. A plurality of raw images are captured with a tilt angle fromthe semiconductor wafer according to graphic data system (GDS)information regarding a layout of a target die, by an inspectionapparatus. A first image-based comparison is performed on the pluralityof raw images, by a determining circuitry, to obtain a defect image inthe plurality of raw images. A second image-based comparison isperformed on a reference image and the defect image, so as to classify adefect type of an image difference in the defect image, by thedetermining circuitry. The number of the plurality of raw images isgreater than 2.

In some embodiments, a method for diagnosing a semiconductor wafer isprovided. By using a determining circuitry, a first image-basedcomparison is performed on a plurality of raw images capturednon-vertically from a plurality of positions of the semiconductor waferaccording to a layout of a target die, so as to detect whether an imagedifference is present between the plurality of raw images. The raw imagehaving the image difference is assigned as a defect image. By using thedetermining circuitry, a second image-based comparison is performed on areference image of a golden wafer and the defect image, so as toclassify a defect type of the image difference. The number of theplurality of raw images is greater than 2.

In some embodiments, a system for diagnosing a semiconductor wafer isperformed. The system includes a processing circuitry, an inspectionapparatus, and a determining circuitry. The processing circuitry isconfigured to provide graphic data system (GDS) information of layout ofa target die. The inspection apparatus is configured to capture aplurality of raw images with a tilt angle from the semiconductor waferaccording to the GDS information from the processing circuitry. Thedetermining circuitry is configured to receive the plurality of rawimages from the inspection apparatus, and to perform a first image-basedcomparison on the plurality of raw images to obtain a defect image inthe plurality of raw images. The determining circuitry is configured toperform a second image-based comparison on a reference image and thedefect image, so as to classify a defect type of an image difference inthe defect image. The number of the plurality of raw images is greaterthan or equal to 3.

The foregoing outlines features of several embodiments so that thoseskilled in the art may better understand the aspects of the presentdisclosure. Those skilled in the art should appreciate that they mayreadily use the present disclosure as a basis for designing or modifyingother processes and structures for carrying out the same purposes and/orachieving the same advantages of the embodiments introduced herein.Those skilled in the art should also realize that such equivalentconstructions do not depart from the spirit and scope of the presentdisclosure, and that they may make various changes, substitutions, andalterations herein without departing from the spirit and scope of thepresent disclosure.

What is claimed is:
 1. A method for diagnosing a semiconductor wafer,comprising: capturing a plurality of raw images with a tilt angle fromthe semiconductor wafer according to graphic data system (GDS)information regarding a layout of a target die, by an inspectionapparatus; performing a first image-based comparison on the plurality ofraw images, by a determining circuitry, to obtain a defect image in theplurality of raw images; performing a second image-based comparison on areference image and the defect image, so as to classify a defect type ofan image difference in the defect image, by the determining circuitry,wherein the number of the plurality of raw images is greater than
 2. 2.The method as claimed in claim 1, further comprising: determiningwhether the classified defect type has effect on a die of thesemiconductor wafer corresponding to the defect image.
 3. The method asclaimed in claim 1, wherein capturing the plurality of raw images withthe tilt angle from the semiconductor wafer according to the GDSinformation of the layout further comprises: capturing a first raw imageof the plurality of raw images from a first position in a first die ofthe semiconductor wafer; capturing a second raw image of the pluralityof raw images from a second position in a second die of thesemiconductor wafer; and capturing a third raw image of the plurality ofraw images from a third position in a third die of the semiconductorwafer, wherein the first, second, and third dies have individualcoordinates in the semiconductor wafer, wherein the first, second, andthird positions correspond to the same coordinates of the target die. 4.The method as claimed in claim 1, wherein capturing the plurality of rawimages with the tilt angle from the semiconductor wafer according to theGDS information of the layout further comprises: capturing a first rawimage of the plurality of raw images from a first position in a firstdie of the semiconductor wafer; capturing a second raw image of theplurality of raw images from a second position in the first die of thesemiconductor wafer; and capturing a third raw image of the plurality ofraw images from a third position in the first die of the semiconductorwafer, wherein the first, second, and third positions have individualcoordinates in the first die.
 5. The method as claimed in claim 1,wherein the GDS information comprises information regarding coordinatesand patterns prone to defects in the layout of the target die
 6. Themethod as claimed in claim 1, wherein the plurality of raw images arecaptured from the semiconductor wafer via optical, electron beam, UVlight, visible light, invisible light, or laser surface scan.
 7. Themethod as claimed in claim 1, wherein the plurality of raw images exceptthe defect image are free of the image difference.
 8. The method asclaimed in claim 1, wherein the layout comprises a multi-layer structureof the target die.
 9. A method for diagnosing a semiconductor wafer,comprising: performing, using a determining circuitry, a firstimage-based comparison on a plurality of raw images capturednon-vertically from a plurality of positions of the semiconductor waferaccording to a layout of a target die, so as to detect whether an imagedifference is present between the plurality of raw images; assigning theraw image having the image difference as a defect image; and performing,using the determining circuitry, a second image-based comparison on areference image of a golden wafer and the defect image, so as toclassify a defect type of the image difference, wherein the number ofthe plurality of raw images is greater than
 2. 10. The method as claimedin claim 9, further comprising: determining whether the classifieddefect type has effect on a die of the semiconductor wafer correspondingto the image difference.
 11. The method as claimed in claim 9, furthercomprising: capturing a first raw image of the plurality of raw imagesfrom a first position in a first die of the semiconductor wafer;capturing a second raw image of the plurality of raw images from asecond position in a second die of the semiconductor wafer; andcapturing a third raw image of the plurality of raw images from a thirdposition in a third die of the semiconductor wafer, wherein the first,second, and third dies have individual coordinates in the semiconductorwafer, wherein the first, second, and third positions are determinedaccording to graphic data system (GDS) information regarding layout ofthe target die.
 12. The method as claimed in claim 9, wherein the layoutof the target die comprises a circuit with a duplicate layout formed bya plurality of same cells,
 13. The method as claimed in claim 9, furthercomprising: capturing a first raw image of the plurality of raw imagesfrom a first position in a first die of the semiconductor wafer;capturing a second raw image of the plurality of raw images from asecond position in the first die of the semiconductor wafer; andcapturing a third raw image of the plurality of raw images from a thirdposition in the first die of the semiconductor wafer, wherein the first,second, and third positions have individual coordinates in the firstdie.
 14. A system for diagnosing a semiconductor wafer, comprising: aprocessing circuitry configured to provide graphic data system (GDS)information of layout of a target die; an inspection apparatusconfigured to capture a plurality of raw images with a tilt angle fromthe semiconductor wafer according to the GDS information from theprocessing circuitry; and a determining circuitry configured to receivethe plurality of raw images from the inspection apparatus, and toperform a first image-based comparison on the plurality of raw images toobtain a defect image in the plurality of raw images, wherein thedetermining circuitry is configured to perform a second image-basedcomparison on a reference image and the defect image, so as to classifya defect type of an image difference in the defect image, wherein thenumber of the plurality of raw images is greater than or equal to
 3. 15.The system as claimed in claim 14, wherein the layout comprises amulti-layer structure of the target die.
 16. The system as claimed inclaim 14, wherein the GDS information comprises information regardingcoordinates and patterns prone to defects in the layout of the targetdie.
 17. The system as claimed in claim 14, wherein the inspectionapparatus is configured to capture a first raw image of the plurality ofraw images from a first position in a first die of the semiconductorwafer, a second raw image of the plurality of raw images from a secondposition in a second die of the semiconductor wafer, and a third rawimage of the plurality of raw images from a third position in a thirddie of the semiconductor wafer, wherein the first, second, and thirdpositions correspond to the same coordinates of the target die.
 18. Thesystem as claimed in claim 14, wherein the inspection apparatus isconfigured to capture the plurality of raw images from a first position,a second position and a third position in the same die of thesemiconductor wafer, wherein the first, second, and third positions haveindividual coordinates in the first die.
 19. The system as claimed inclaim 14, wherein the inspection apparatus is configured to capture theplurality of raw images via optical, electron beam, UV light, visiblelight, invisible light, or laser surface scan.
 20. The system as claimedin claim 14, wherein the plurality of raw images except the defect imageare free of the image difference.